3D GIS Semi-automatized Modelling Procedure for the Conservation of the PHiM: Heritage Municipal Buildings of Seville (Spain): a New Dimension for Urban Cultural Data Management

17 3D GIS Semi-automatized Modelling Procedure for the Conservation of the PHiM: Heritage Municipal Buildings of Seville (Spain). A New Dimension for Urban Cultural Data Management FRANCISCO M. HIDALGO-SÁNCHEZ, Universidad de Sevilla Escuela Técnica Superior de Ingeniería de Edificación, Construcciones Arquitectónicas II Sevilla, Andalucía, ES EMILIO J. MASCORT-ALBEA, Universidad de Sevilla Escuela Técnica Superior de Arquitectura, Estructuras de la Edificación e Ingeniería Del Terreno Avenida de Reina Mercedes 2 Sevilla, Andalucía, ES 41012 MARTIN KADA, Technische Universitat Berlin Fakultat VI Planen Bauen Umwelt, Institut für Geodäsie und Geoinformationstechnik Berlin, Berlin, DE ROCÍO ROMERO-HERNÁNDEZ, Universidad de Sevilla Escuela Técnica Superior de Arquitectura, Estructuras de la Edificación e Ingeniería del Terreno Avenida de Reina Mercedes 2 Sevilla, Andalucía, ES 41012 JACINTO CANIVELL, Universidad de Sevilla Escuela Técnica Superior de Ingeniería de Edificación, Construcciones Arquitectónicas II Sevilla, Andalucía, ES FRANCISCO LÓPEZ-LARRÍNAGA, Ayuntamiento de Sevilla, Gerencia de Urbanismo y Medioambiente, Infraestructura de Datos Espaciales de Sevilla, Sevilla, Andalucía, ES This research explores the possibilities resulting from the use of three-dimensional (3D) models designed in GIS environments for their application to the management and conservation of historical architectonic heritage. This 3D modelling work is one of the strategic actions of the recently finished Master Plan for Conservation of Heritage Municipal Buildings (PD-PHiM) for the City of Seville (Spain). This plan deals with the analysis of a group of 115 municipally owned buildings of high heritage interest that include different typologies, chronologies scales, and uses. This investigation has complemented and continued the initial work begun by the Seville Spatial Data Infrastructure (ide.SEVILLA) in the field of 3D mapping of urban environments and its publication as institutional open data. The implemented improvements started on an initial diagnosis of a preliminary urban model, which reached a level of detail (LOD) of 2, as defined by the CityGML standard, in only 20% of the registered assets in the PD-PHiM database. The The research and writing of this article were supported by a Grant for the International Mobility of Research Staff from the VI Own Research Plan of the University of Seville for 2020 (VI PPI-US, 2020). Authors’ addresses: F. M. Hidalgo-Sánchez, Universidad de Sevilla Escuela Técnica Superior de Ingeniería de Edificación, Construcciones Arquitectónicas II Sevilla, Andalucía, ES Avenida de Reina Mercedes 4A Sevilla, Andalucia, ES 41012; email: [email protected]; E. J. Mascort-Albea (corresponding author) and R. Romero-Hernández, Universidad de Sevilla Escuela Técnica Superior de Arquitectura, Estructuras de la Edificación e Ingeniería del Terreno Avenida de Reina Mercedes 2 Sevilla, Andalucía, ES 41012; emails: {emascort, rociorome}@us.es; M. Kada, Technische Universitat Berlin Fakultat VI Planen Bauen Umwelt, Institut für Geodäsie und Geoinformationstechnik Berlin, Kaiserin-Augusta-Allee 104-106, 10553 Berlin; email: [email protected]; J. Canivell, Universidad de Sevilla Escuela Técnica Superior de Ingeniería de Edificación, Construcciones Arquitectónicas II Sevilla, Avenida de Reina Mercedes 4A Sevilla, Andalucia, ES 41012; email: [email protected]; F. López-Larrínaga, Ayuntamiento de Sevilla, Gerencia de Urbanismo y Medioambiente, Infraestructura de Datos Espaciales de Sevilla, Av. Carlos III, S/N, 41092 Sevilla; email: [email protected]. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]. © 2022 Association for Computing Machinery. 1556-4673/2022/01-ART17 $15.00 https://doi.org/10.1145/3467976 ACM Journal on Computing and Cultural Heritage, Vol. 15, No. 1, Article 17. Publication date: January 2022. 17:2 • F. M. Hidalgo-Sánchez et al. proposed methodology has achieved the automation of most of the process of building 3D geo-referenced models to increase the percentage of assets that reach the LOD2 to 75%. The initial information comes from the use of institutional spatial data of different types and sources: Light Detection and Ranging (LiDAR), Spanish Cadastre Office, and so on. Additionally, the generated entities have been linked to a complex, multidisciplinary and multiscale database, designed within the framework of the strategic actions of the PD-PHiM. The contributions of the proposal, especially in the automation of processes, imply a considerable saving of resources in comparison with other methods in which the modelling is eminently carried out manually. Thus, they are complementary to those that are related to the use of 3D modelling software intended for other purposes, with the consequent incompatibilities and hard interoperability procedures with GIS environments that this implies. CCS Concepts: • Information systems →Geographic information systems;•Computing methodologies →Pointbased models;•Applied computing → Computer-aided design; Additional Key Words and Phrases: LiDAR, cultural heritage, interactive models, LOD2 ACM Reference format: Francisco M. Hidalgo-Sánchez, Emilio J. Mascort-Albea, Martin Kada, RocÍo Romero-Hernández, Jacinto Canivell, and Francisco López-Larrínaga. 2022. 3D GIS Semi-automatized Modelling Procedure for the Conservation of the PHiM: Heritage Municipal Buildings of Seville (Spain). A New Dimension for Urban Cultural Data Management. J. Comput. Cult. Herit. 15, 1, Article 17 (January 2022), 25 pages. https://doi.org/10.1145/3467976 1 INTRODUCTION The Master Plan for Conservation of Heritage Municipal Buildings—Plan Director de Patrimonio Histórico inmueble Municipal (PD-PHiM)—is a strategic document recently published at the initiative of the Seville City Council, intending to promote a specific line of heritage protection for the assets it owns. Its necessity was determined by the urgent requirement that many buildings and heritage sites, whether in use or closed to the public, have to be restored and brought into line with minimum conditions of use. It also addresses the need to diagnose the current state of conservation and assess the maintenance costs of many municipally owned buildings. The actions established in the PD-PHiM foster a policy of protection of a transversal and inclusive character. This approach is capable of enhancing this heritage in the context of the contemporary city and of optimising the management of current resources, employing a better knowledge about them. Master plans, as integrated management programmes for monumental complexes, are widely known and utilised [Mauro 2019]. Nevertheless, there are not many precedents for their application to the integrated management on an urban scale of such a wide and heterogeneous group of heritage sites as the historic buildings belonging to the city of Seville. Accordingly, the design of the PD-PHiM has included 115 cultural assets in its final catalogue. These comprise not only buildings that show very different states of conservation, chronology, typology, construction technique, and uses but also movable assets and archaeological sites with their own heritage features (Figure 1). In this sense, a special feature of the PD-PHiM is that it is not conceived as a compilation of specific master plans applied to individual assets; rather, it is a document that provides comprehensive diagnostics. Consequently, the aim of this research is not to evaluate the particularities of these assets but rather to highlight the dimension and complexity of the heritage site considered as a case study. The aforementioned starting conditions challenge the use of new digital geo-spatial management tools to control the information related to the urban heritage. According to these needs, the PD-PHiM has proposed the creation of a digital data repository called the Municipal Historical Heritage Information System of Seville (Sistema de Información del Patrimonio Histórico Municipal de Sevilla, SIPHiM). By using geographic information ACM Journal on Computing and Cultural Heritage, Vol. 15, No. 1, Article 17. Publication date: January 2022. 3D GIS Semi-automatized Modelling Procedure for the Conservation of the PHiM • 17:3 Fig. 1. Typological identification of the 115 assets included in the PD-PHiM, located on a map of the city of Seville. ACM Journal on Computing and Cultural Heritage, Vol. 15, No. 1, Article 17. Publication date: January 2022. 17:4 • F. M. Hidalgo-Sánchez et al. systems (GIS), the SIPHiM has been incorporated into the Spatial Data Infrastructure of Seville (Infraestructura de Datos Espaciales de Sevilla, ide.SEVILLA). The creation of SIPHiM has enabled a centralised and transversal approach to the management of a massive dataset of catalogued assets. These have been organised into four categories: A., Identification; B., Documentation; C., Diagnosis; and D., Intervention. They have been further categorized into 12 blocks, as follows: A.I., General Information; A.II., Protection; B.III., Sources and Bibliographies; B.IV., Archaeology; C.V., Conservation; C.VI., Maintenance; D.VII., Space Management; D.VIII., Training; D.IX., Networks; D.X., Projects; D.XI., Sponsorship; and D.XII., Creative Industries. The information provided by each of the blocks has been employed to semantically enrich the graphic entities generated for the project. Through a powerful spatial and thematic normalization work concerning to the SIPHiM database, a set of digital models has been designed to be published and used as a powerful tool for governance at a local level. The set of models generated is composed of multiscale thematic two-dimensional (2D) cartographies and three-dimensional (3D) models that reach a level of detail (LOD) of 2, as defined by the CityGML standard [Gröger and Plümer 2012]. The choice of the LOD2 responds to its sufficiency to achieve the main objective of this research: to generate a 3D urban model with standardised semantic information associated to the 115 assets included in the PD-PHiM, allowing the accurate visual recognition of these through their geometry. 1.1 Local Spatial Data for Heritage Management: ide.SEVILLA The spatial data governance of the city has been developed by ide.SEVILLA in the past several years. This platform is integrated into the Spatial Data Infrastructure of Spain (Infraestructura de Datos Espaciales de España, IDEE). Its purpose is to provide access to the data, metadata, and geographical services produced by the city of Seville. This geo-portal was conceived as an open data institutional platform that makes available to citizens the geographic information generated at the local level. Therefore, it promotes e-government, emphasising the accessibility, dissemination, use, and interoperability of published data. By using GIS tools, ide.SEVILLA allows users to consult and access a wide variety of content of different topics and formats, which are generally designed for viewing as interactive 2D cartography through mobile and web applications. Additionally, due to the breadth of the heritage of Seville, its managers have for years been encouraging the development of projects specifically linked to promote a better understanding of the values of the architecture and heritage of the city [Mascort-Albea et al. 2016]. The works performed in this area have brought them several prizes and recognition at the national level. In this sense, the PD-PHiM is the most recent heritage project to be launched regarding a topic in which ide.SEVILLA holds a remarkable background. This work establishes the first experience of the geo-portal in the development of 3D models for the spatial data management of heritage buildings. The main approaches and research results obtained in this work are presented in the next sections. 2 GIS-3D FOR CULTURAL HERITAGE SITES The continuous progress of disciplines such as topography, computing, and digital content delivery generates new methodologies related to the knowledge of cultural heritage. This type of development allows not only researchers but also students, tourists, and citizens in general to use a wide range of new tools to obtain information and carry out analyses related to the history of art, architecture, and archaeology. One of these new possibilities is the development of 3D digital environments with different levels of detail that simulate real buildings. Such models can be linked to external data, acting as repositories of different types of information, so that their function goes beyond visualisation purposes, allowing queries and analysis to be carried out using GIS tools (sometimes via web-enabled services). ACM Journal on Computing and Cultural Heritage, Vol. 15, No. 1, Article 17. Publication date: January 2022. 3D GIS Semi-automatized Modelling Procedure for the Conservation of the PHiM • 17:5 The traditional use of 2D spatial data remains effective for many purposes. Nevertheless, the use of 3D models provides a field of possibilities that is difficult to achieve through other methodological approaches. The introduction of a new dimension implies a significant improvement in visualisation—most importantly, it makes it possible to carry out analyses that take into account new spatial attributes of the architecture itself and its environment. Currently, research that focuses on the use of 3D models based on heritage buildings in GIS environments can be classified into two main categories, differentiated by the scale of the heritage complex that they simulate. Firstly, there is a trend towards the creation of 3D models of a singular building or, occasionally, a reduced set of them. The main purpose for creating this type of model is usually related to obtaining technical information for the conservation, maintenance, and risk management of the concerned building [Amirebrahimi et al. 2015; Lezzerini et al. 2016; Colucci et al. 2018]. In such cases, the workflow implemented for the creation of the 3D model usually comprises the construction of the model with non-GIS tools and its subsequent insertion into GIS environments through interoperability procedures [Apollonio et al. 2010; Centofanti et al. 2012]. Mixing with disciplines such as Building Information Modelling (BIM) is common [Almeida et al. 2016; Dore and Murphy 2012; Matrone et al. 2019; Tobiáš and Cajthaml 2020], but this type of interoperability between BIM and GIS is not yet completely successfully [Hidalgo Sánchez 2018; Mascort-Albea et al. 2019]. Additionally, there are remarkably numerous contributions that focus on the creation of mediumand largescale urban environment 3D models [Álvarez et al. 2018; Larsson 2017;Lee2018; Prieto et al. 2014; Chevrier 2015]. Nonetheless, the percentage of research focused on simulating environments with heritage value on this scale is still not particularly important [Biljecki et al. 2015]. The aim of the aforementioned studies is usually to analyse these sets from a global perspective, allowing detailed analyses to be carried out if required. In these cases, the 3D models are usually created directly using GIS tools [Haala and Kada 2010;Kada2019; Wichmann et al. 2019] and a web-based interface [Agugiaro et al. 2011; Jovanović et al. 2020]. Despite their different scales and purposes, both methodologies frequently coincide in the way that they acquire the initial data [Remondino and Agugiaro 2014]. Generally, most of the established approaches use techniques based on image data [Remondino et al. 2009], range data [Vosselman and Maas 2010], classical surveying or existing maps [Yin et al. 2009], or a combination of these. Regarding this aspect, the final decision usually depends on the required accuracy, the object’s dimensions and location, the characteristics of its surface, the experience of the team, and the available resources. The application of a technique will result in data with different resolutions, both at the geometric and texture level, which can be utilised to create 3D models with different LODs depending on the specific purpose of the research. It should also be noted that in the field of cultural heritage, the use of 3D models in GIS environments is widespread in disciplines such as Archaeology both on a small scale [Forte 2014] and a large scale [Dell’Unto et al. 2016]. 3 TOWARDS A 3D-GIS MODEL OF THE CITY OF SEVILLE IN THE FRAMEWORK OF THE PD-PHIM In recent years, ide.SEVILLA has made an effort to incorporate 3D data production into the platform’s services that can be managed and published for different purposes. One of its main aims is to create a 3D model of the city being used on the one hand as an urban management tool and on the other to share the results as open data. With this purpose, ide.SEVILLA has developed several preliminary 3D urban models based on institutional data (Light Detection and Ranging [LiDAR], cadastral and geographical services, etc.) and through the employment of the software, licences, and services provided by ESRI (ArcGIS Desktop and Pro, ESRI City Engine, etc.). The latest version of these 3D models was used as the starting point for this research, which, thanks to the partnership and resources provided by the institutional geo-portal, has achieved notable quantitative and qualitative improvements in the formalization of the 3D entities corresponding to the catalogued assets in the PD-PHiM. ACM Journal on Computing and Cultural Heritage, Vol. 15, No. 1, Article 17. Publication date: January 2022. 17:6 • F. M. Hidalgo-Sánchez et al. Fig. 2. Preliminary diagnostic mapping of the starting 3D model, depicting the LOD of the PD-PHiM recorded assets. The proposed methodology is essentially a three-phase approach, comprising six stages, with an iterative process that allows for cyclical improvements in the achieved results. Firstly, a diagnosis has been carried out of the 115 heritage buildings selected from the preliminary starting model based on their LOD. Secondly, a semi-automatic procedure has been established to model these graphic entities with a higher LOD, taking the formal typological characteristics of the historic buildings into account. Finally, the operational database created for SIPHiM has been integrated into the new 3D model, which can be consulted through the Seville City Council’s ArcGIS Online platform pending the development of future specific applications for its dissemination. The resulting new model will constitute the new starting point for the implementation of a future improvement cycle based on the proposed methodology. 3.1 Preliminary 3D Model Diagnosis The assessment of the preliminary model constitutes the unique stage of this phase and made it possible to determine the LOD that the 115 assets included in the PD-PHiM showed individually. The detailed diagnosis of each asset has been recorded in a database that allows the creation of a diagnostic map, updated in real-time (Figure 2). This cartography indicates the LOD of the model corresponding to each asset. The diagnosis also checked other complementary issues: sector of the city, conditions of the cadastral plot, and situations related to the existence of movable assets and archaeological ruins among the catalogued records. To establish the features of each LOD, the criteria normally used for the CityGML standard [Gröger and Plümer 2012] were adopted. Five categories were established: LOD0 to LOD4: ACM Journal on Computing and Cultural Heritage, Vol. 15, No. 1, Article 17. Publication date: January 2022. 3D GIS Semi-automatized Modelling Procedure for the Conservation of the PHiM • 17:7 •LOD0: Corresponds to a Digital Terrain Model (DTM 2.5) that represents buildings as 2D entities. •LOD1: Buildings are shown as simple prisms to which their height has been defined. •LOD2: The buildings present geometries of the roofs, being able to show other main elements of the volume. •LOD3: The buildings include compositional elements of the facades: windows, doors, dormers, and more. •LOD4: This is the highest LOD, adding detailed interiors to the previous level. Through the preliminary diagnosis, it was determined that the city’s urban model was a remarkable starting point but did not achieve the objectives of the PD-PHiM. Through the 3D modelling action, the majority of the catalogued buildings had to reach LOD2. Accordingly, only 22 entities fulfilled this requirement; therefore, only 19% of the total number of buildings could be recorded as LOD2. Furthermore, 53% of the registered buildings (61 properties) were represented by LOD1, and the percentage of LOD0 elements, that is, without 3D geometry, was 28% (32 properties). In a complementary way, it was detected that the semantic information linked to the graphic entities was practically nonexistent. Several reasons could be found to explain the small number of modelled buildings reaching LOD2. The main causes of these shortcomings are related to the unique geometry of certain buildings and to the typological diversity in the PD-PHiM inventory as well as to the data and techniques that were used to create this model. Many of these issues were resolved through the development of the methodological phase described next. 3.2 Semi-automatic Procedure for GIS-3D Modelling of Historical Buildings This working phase contains three main methodological stages: analysis of the model’s requirements and data acquisition by using institutional sources; processing and filtering of the information for the different operating formats; and development of the 3D model according to the LOD0, LOD1, and LOD2 levels of detail. 3.2.1 Data Acquisition. The use of open data for the development of the urban 3D model includes the following sources and formats: •2D vectorial data on ESRI Shapefile Format (SHP): Provided by the General Cadastre Department (Dirección General del Catastro, DGC) and downloaded from the Electronic Office of this institution. •2D vectorial data on CAD Drawing Exchange Format (DXF, DWG): Obtained from the cartographic database of ide.SEVILLA and provided by GUMS technicians. •Digital orthophotos of flights from the National Plan for Aerial Orthography (Plan Nacional de Ortofotografía Aérea, PNOA): Downloaded from the metropolitan area of Seville via the National Centre for Geographical Information (Centro Nacional de Información Geográfica, CNIG). •Digital point cloud files captured with LiDAR sensors during 2014, in compressed data format (LAS, LAZ): provided by PNOA coverage and downloaded from CNIG, they have a density of 0.5 points/m2,amesh spacing of 5 m, and an estimated altimetric accuracy ≤0.3 m. 3.2.2 Data Processing. The extensive scale of the complete urban 3D-GIS model, corresponding to a total area of 140.80 km2, implies that its elaboration has been performed in a sectorized approach. With this strategy, the resulting files are smaller in size, the processing time is shorter, and the resources used are optimised. To achieve the proposed segmentation, the division into sectors of the CNIG’s LiDAR data coverage has been taken as a reference. Likewise, priority has been given to selecting and modelling the sectors that comprise assets included in the PD-PHiM. Complementarily, the sectors which do not contain assets but ensure the continuity of the urban model with them have also been modelled (Figure 3). The following sections are an illustrative example of the applied procedures in sector 9. This sector, which covers a significant part of Seville’s historical centre, has been chosen as a highly representative sample of the developed work. Thus, it ACM Journal on Computing and Cultural Heritage, Vol. 15, No. 1, Article 17. Publication date: January 2022. 17:8 • F. M. Hidalgo-Sánchez et al. Fig. 3. Sectors considered for the development of the PD-PHiM assets’ 3D model based on the zoning for downloading LiDAR data in Seville, provided by the CNIG. *Assets that share sectors. **Sectors with different reference system. The following sections illustrate the applied procedures in sector 9, highlighted in red. involves a high percentage of the 115 buildings which make up the case study and shows a notable typological variety among the selected assets. Additionally, it is necessary to indicate that the following software listed below has been used to process and edit the gathered data, differentiating between free software (FS) and licensed software (LS): •LAStools (FS): Used for LiDAR data decompression. •QGIS (FS): Employed for 2D GIS data management. •ESRI ArcGIS Pro (LS), licensed by ide.SEVILLA support: Applied for LiDAR data management, generation of raster files (DTM, DSM, and nDSM) and control of 3D-GIS data. Its ArcGIS Pro Local Government 3D Basemaps project template, which includes pre-configured tasks and tools, has streamlined the process of building the 3D model in its various LODs. •AutoCAD Map 2019 (LS), with an academic license provided by the University of Seville: Used for processing CAD data of buildings. 3.2.2.1 LiDAR Data. LiDAR points stored in LAS files are usually classified into different classes using specialised classification tools which group the points according to the nature of the entities that they represent. This task is usually carried out by the data provider. In this case, the point cloud downloaded from the CNIG and coming from the PNOA has already gone through a point classification process. While it is true that the initial point classification is not completely accurate [García Rodríguez 2019], the estimated errors are not of particular relevance for the purpose of this research, which works on an urban scale and aims for LOD2 accuracy. For this reason, it is not considered necessary to carry out new processing of the LiDAR data source used, preserving the initial classification. The preliminary classification of LAS files from PNOA is based on the standards of the American Society for Photogrammetry and Remote Sensing (ASPRS) and using the Point Data Record Format 3 of the ASPRS LAS version 1.2 Format Specification [ASPRS 2008]. This classification is based on a standardised approach and is shown in Table 1. Once the LiDAR data have been decompressed into LAZ format using LAStools software, it is obtained as LAS data that are compatible with ArcGIS Pro software. The geoprocessing tool “Create LAS Dataset” generates an ACM Journal on Computing and Cultural Heritage, Vol. 15, No. 1, Article 17. Publication date: January 2022. 3D GIS Semi-automatized Modelling Procedure for the Conservation of the PHiM • 17:9 Table 1. LAS Specification Standard Points Classification in LiDAR Data According to ASPRS, Version 1.2 Classification Value Meaning Classification Value Meaning 0 Created, never classified 7 Low Point (noise) 1 Unclassified 8 Model Key-point (mass point) 2Ground 9 Water 3 Low Vegetation 10 Reserved for ASPRS Definition 4 Medium Vegetation 11 Reserved for ASPRS Definition 5 High Vegetation 12 Overlap Points 6 Building 13–31 Reserved for ASPRS Definition Fig. 4. LAS Dataset statistics corresponding to sector 9. The classification codes assigned by CNIG to the points are the same as those of the ASPRS LAS 1.2 Format Specification (ASPRS 2008). LAS Dataset that can be edited and viewed. This tool is also used to calculate statistical information from the LAS Dataset created. Additionally, the altimetric datum of each record is transformed from ellipsoidal to orthometric heights. Following these initial steps, it is recommended to verify that the points are classified and that this classification is correct. The verification is carried out in two ways. Firstly, the LAS Dataset statistics are checked. The correspondence of the LAS Dataset classification codes (Figure 4) with the ASPRS classification shown in Table 1 can be observed. As Figure 4shows, the number of points assigned to class 12 “Overlap/Reserved” is remarkable. During data capture, several passes are made on different days. Occasionally, in each of these passes, differences in the height values of certain points are found. When this happens, the criterion normally followed is that the point with the highest scan angle is classified as “Overlap” and the others are classified in their corresponding class. To avoid errors in subsequent processing, this class of points will be filtered out. Secondly, by selecting some representative points and consulting the data concerning the “Class code” in the pop-up window, it is possible to check the correspondence with the classification in Table 1. During this checking process, it is common to find outliers in the elevation value scale of an LAS Dataset. In this sense, it is usual to find some anomalous points (generally coinciding with birds or air vehicles) which are captured during the data collection flights and classified as “noise”. These points can significantly modify the elevation values, both above ACM Journal on Computing and Cultural Heritage, Vol. 15, No. 1, Article 17. Publication date: January 2022. 17:16 • F. M. Hidalgo-Sánchez et al. Fig. 8. Macarena Ramparts 3D modelling, asset No. 16 PD-PHiM. Top, Automatic output. Bottom, Hand-refined model. The comparison between the roof shape layer and the geo-referenced digital orthophoto is also shown. 3.3.1 SIPHiM Operational Data Integration. As a preliminary step, a new field has been created to identify the 115 entities that make up the PD-PHiM. Thanks to the information incorporated in this field, the layer of 3D entities can be symbolised to highlight the buildings belonging to the case study. Once the elements have been identified, the PD-PHiM assets have been linked to the information corresponding to the SIPHiM block A.I., General Information (Table 2). SIPHiM information is linked to entities through the Join geoprocessing tool. By joining tables with a common field, in this case, REFCAT, the information of the theme block is associated with the 3D entities. ACM Journal on Computing and Cultural Heritage, Vol. 15, No. 1, Article 17. Publication date: January 2022. 3D GIS Semi-automatized Modelling Procedure for the Conservation of the PHiM • 17:17 Table 2. Data Fields Corresponding to SIPHiM Block A.I., General Information INIDE_DE_1 Main name A.I.1, Identification INIDE_DE_2 Other names INIDE_DIR Address INIDE_REFCAT Cadastral reference A.I.2, Description INDES_TI_1 General typology INDES_TI_2 General typology INDES_CURB Urban Planning Class INDES_CRON Chronology INDES_AUTR Author INDES_DESC General description INDES_HIST Historic evolution INDES_FTMU Municipal purchase date INDES_MOD Municipal purchase mode INUA_US_1 Main and current use 1 A.I.3Uses and activities INUA_US_1_G Use 1 manager INUA_US_2 Secondary uses 2 INUA_US_2_G Uses 2 managers INUA_US_H Main historical use INUA_CR_H Secondary historical uses INUA_ACTVD Activities INUA_ESP_C Cession to other owners INUA_ESP_A Renting spaces INUA_VISIT Visiting hours INUA_WEB Website address INUA_TELEF Telephone number Fig. 9. Consulting information from the PHiM’s 3D entities. Before this last step, it is recommended to unify the 3D entity layers of all sectors into a single layer so that the process needs to be carried out on only one occasion. This unification will speed up the process of publishing the scene as a web layer. Finally, after exporting the new layer of 3D entities with thematic information, the displayable fields have been configured. By hiding, ordering, and assigning an alias to the different fields, a better interpretation of the information shown in the pop-up window is achieved (Figure 9). 3.3.2 Publication of Results on ide.SEVILLA. This section develops the process of publishing the contents of the 3D-GIS LOD2 model finally obtained as well as the elevation surface generated. Additionally, some considerations for the future updating of the model are provided. ACM Journal on Computing and Cultural Heritage, Vol. 15, No. 1, Article 17. Publication date: January 2022. 17:18 • F. M. Hidalgo-Sánchez et al. 3.3.2.1 Publication of LOD0 DTM Elevation Surface. If the elevation surface created from the DTM is shared as a web layer, the base of the web scene will correspond to the elevation of the published buildings. For this purpose, the pre-configured task Publish Elevation Surface has been applied. In this case, to obtain a unique elevation surface that includes all sectors of the initial LiDAR coverage that have been modelled, the necessary steps to obtain a new DTM have been replicated. The difference in this case is that the LAS Dataset used must include all of the files of the modelled sectors to generate a raster DTM only. After obtaining this new DTM, the first step is to convert the units from feet to meters. If they are already converted, this step can be omitted. For reprojecting the DTM, WGS_1984_Web_Mercator_Auxiliary_Sphere has been set as the output coordinate system. If the geographic transformation is not automatically detected by the tool, it must be selected from the list. In this case, ETRS_1989_To_WGS_1984 is chosen. The remaining parameters have been kept before running the geoprocessing tool. Once obtained, the projected raster DTM can be added to the scene as a new elevation surface and shared as a web layer. During this operation, the following parameters must be established for its publication. •Ordering tiles scheme: Same as the base map. •Levels of detail (referred to the visualization scale): 0 (world)–20 (buildings). •Temporary cache location: Roof_Form_Extraction. •Limited Error Raster Compression (LERC): 0.05. Previous to the execution of the publication tool, the data of the elevation area can be configured: name, labels, description, location, and so on. Once the process is complete, the elevation surface can be viewed in the ArcGIS Online Scene Viewer or downloaded for viewing in ArcGIS Pro. 3.3.2.2 Publication of Buildings 3D Entities. The dataset generated from the 3D model works as a type of 2D entity that is rendered to show 3D geometries. For this reason, if it is published in this format, the file must be re-symbolised and can only keep its 3D shape with the exact symbology specifications of the layer file that was processed. Consequently, the publication process of the PD-PHiM entities requires the transformation of the dataset of the 3D model into a multi-patch file that allows the conservation of the 3D geometry of the generated entities. Additionally, the necessity of transforming the coordinates to the WGS 84 projection system for correct publication is recalled again. This adjustment is essential if the layer is to be displayed in global scenes and local scenes with ESRI base maps. The publication of the file as a 3D multi-patch entity has been done through the pre-configured Publish Buildings task and its included tools. Through them, this file can be shared as a web layer, controlling the internal configuration of the data in the same way as it was done with the DTM in the previous step. Once this last step has been achieved, the model can be consulted as a web service through the ArcGIS Online platform (Figure 10). Trying to display the layer in ArcGIS Online immediately after it is published may result in the message “Root node missing in scene service”. When publishing a web scene layer that contains more than one ArcGIS Pro multipatch layer, ArcGIS Pro returns a message that the scene cache has been generated successfully, even if only the first multi-patch layer cache has been generated. If attempts are made to open the scene layer immediately in the scene viewer and not all caches are generated, this error will appear. In this case, it is necessary to allow a little more time to generate the cache of the multi-patch layer before trying to open the web scene layer. 3.3.2.3 3D-GIS LOD2 Model Updating. One of the characteristics of the proposed methodology is its iterative nature. It is very important to generate clear and comprehensible knowledge structures, which will allow future updates of the generated model. Thus, the incorporation of new LiDAR data or more complete thematic information can be executed by automatically updating the model through the Update Schematic Buildings task. This tool carries out the following processes: ACM Journal on Computing and Cultural Heritage, Vol. 15, No. 1, Article 17. Publication date: January 2022. 3D GIS Semi-automatized Modelling Procedure for the Conservation of the PHiM • 17:19 Fig. 10. Web consulting information from the PHiM’s 3D entities. •Comparison of the multi-patch 3D entity layer with future LiDAR datasets to verify whether updates are required due to the existence of urban renewal processes: construction, demolition, and so on. Through this verification, it is possible to obtain a new file of 2D entities in which the changes have been detected according to the configured parameters. •Creation of new LOD2 3D entities updated through the new layer generated. The new LOD2 3D entities can be merged with the existing ones in the original multi-patch 3D entity layer. 3.4 Diagnosis of the 3D-GIS LOD2 Model for the PD-PHiM The evaluation of this model has been performed, as in the case of the preliminary model, based on the LOD with which each of the 115 assets included in the PD-PhiM were modelled (Figure 11). This approach established which of these buildings are modelled in LOD2, which is, together with the semantic enrichment of the model, the main objective of the proposal. To do this, the buildings have been located in the 3D-GIS model and a visual comparison of them has been carried out, focusing on the morphology of the modelled roofs in comparison with their real roofs, the main difference between LOD1 and LOD2. The evaluation concludes with the following results: 21 assets with a LOD0, 10 buildings with a LOD1 level and 85 buildings corresponding to a LOD2 level. In comparison with the initial model of ide.Sevilla, a considerably higher number of buildings modelled in LOD2 has been achieved in relation to the 22 LOD2 assets shown in the preliminary model diagnosis. Finally, the detailed and individualized diagnosis of each PD-PHiM asset has been reflected in a comparative sheet that allows the visualization of the specific modelling results of each asset (Figure 12). Through this work, the current state of the 3D entities representing each of the catalogued assets is established. ACM Journal on Computing and Cultural Heritage, Vol. 15, No. 1, Article 17. Publication date: January 2022. 17:20 • F. M. Hidalgo-Sánchez et al. Fig. 11. Diagnostic results based on the detail level (LOD) of the 3D-GIS model for the PD-PHiM. 4 DISCUSSION OF RESULTS Compared with the preliminary model that has served as the starting point for this research, the new PD-PHiM model has achieved a remarkable increase in the LOD of modelled assets. As the data sources used for both models are similar, the processes of filtering and processing (prior and subsequent) of the generated data have significantly improved the results provided by the preliminary model through automation techniques. In this sense, it can be considered that the proposed methodology has been successful despite the dependence of the results from post-processing being based on manual verification and editing tasks. From a general point of view, the reasons why the number of modelled PHiM assets that reach a LOD2 is so small are the exclusively automated modelling procedure, the specific architectural character of these buildings, and the data on which the model is based. To this question we should add another factor, the significant amount of archaeological assets (many of them are buried sites) included in the PD-PHiM. Consequently, a series of future actions are proposed to achieve a greater LOD in the rendering of the 3D generated entities: •More accurate modelling can be achieved by using higher-precision LiDAR data. Nevertheless, for the initial purpose of generating a 3D-GIS heritage model with linked thematic information, it is necessary ACM Journal on Computing and Cultural Heritage, Vol. 15, No. 1, Article 17. Publication date: January 2022. 3D GIS Semi-automatized Modelling Procedure for the Conservation of the PHiM • 17:21 Fig. 12. 3D modelling results from the PD-PHiM action (I). Colour for buildings: red (LOD0), purple (LOD1), and blue (LOD2). Colour for dots: black (Architectural), grey (Archaeological) and white (Architectural +Archaeological). ACM Journal on Computing and Cultural Heritage, Vol. 15, No. 1, Article 17. Publication date: January 2022. 17:22 • F. M. Hidalgo-Sánchez et al. Fig. 12. (Continued) to consider whether the degree of precision achieved in the buildings that have been modelled is sufficient. Investing resources in higher degrees of accuracy may not necessarily lead to corresponding returns. •The quality of the LiDAR data in the cartographic base also had a significant influence on the global assessment of the buildings that have been modelled. It is obvious that if a building does not appear on the map, there will be no reference for it to be modelled. Considering this issue, a series of reflections and alternatives are proposed. ACM Journal on Computing and Cultural Heritage, Vol. 15, No. 1, Article 17. Publication date: January 2022. 3D GIS Semi-automatized Modelling Procedure for the Conservation of the PHiM • 17:23 One possible solution would be to extract the plots from the LiDAR data, segment them into sub-plots, and thus have the possibility of more building volumes. In this way, a new planimetric base would be obtained which, while not having the same precision as the cadastral base, may contain entities that do not appear in it. Alternatively, the 2D planimetric base provided by the GUMS could be used. Practically all PD-PHiM assets are included in this database. Entities could be extracted from the missing assets and added to the layer of sub-plots. This operation requires a transformation process of the cartography itself to adapt it to the requirements of the modelling methodology: the creation of cadastral boundaries, the assignment of cadastral references (REFCAT) to these entities, and so on. Finally, there is the possibility of manually creating the missing building entities with ArcGIS Pro tools or other software, such as City Engine from ESRI. This is the method that has been successfully applied to modify the built model, obtaining considerable improvements over the initial model in terms of the number of assets modelled and the LOD achieved, as reflected in the statistics provided in the diagnosis of the PD-PHiM model (Section 4.4). •The pre-configured tasks of the Local Government 3D Basemaps solution do not cover all types of PHiM property roofs. The particularity of some of these buildings prevents associating their roofs with the pre-configured types. To address this concern, the possibility of creating procedural rules to model the typical roof types of these traditional buildings has been considered while, in some cases, manual modification of the roofs would still be necessary. Another important improvement provided by the PD-PHiM model concerning the preliminary version is its semantic enrichment. This is due to the incorporation of thematic information from the SIPHiM spatial database, created for this purpose. In this sense, the integration of new blocks of information would represent a significant advance towards the possibility of creating a 3D database aimed at managing and disseminating the heritage values of Seville’s municipal assets. 5 CONCLUSIONS This research has provided an understanding of a comprehensive, replicable and oriented method for the historic buildings that comprise the historic core of the contemporary city. This is achieved through a workflow of three main phases, comprising six stages: preliminary diagnosis, data acquisition, information processing, model generation, semantic enrichment, and data publication. Assuming that automatic processes are the most desirable path to optimise resources related to the production of parametric entities, strategies have been chosen to speed up production and take into account the formal features that this type of cultural asset usually has. This is a research proposal to systematically address a wide range of heritage assets for their integration into a municipal management network that includes 3D urban models. This cannot be considered a final work but instead the beginning of a set of operations encouraged by local governance to achieve a progressive semantic enrichment of the models and an increase in the LOD, aspiring to LOD3 and LOD4 entities, to reach a deep level of operation and use of the institutional model. Additionally, it is necessary to take into account that the numbers and percentages of success achieved in the final results include in the total calculation assets corresponding to very unique architectural types or buried archaeological sites. For particular situations of this type, the automatic procedures still present notable shortcomings; thus, much more specific modelling projects are required. Nevertheless, these approaches often require excessive spending of resources due to the costs for data acquisition, data processing, and subsequent production procedures of the three-dimensional models to reach high levels of detail. When the purpose of the research justifies it, these processes can be a cost-effective option. On other occasions, however, achieving such a high LOD—and, therefore, technical definition—can be counterproductive to the operation of projects of a more generalist nature. ACM Journal on Computing and Cultural Heritage, Vol. 15, No. 1, Article 17. Publication date: January 2022. 17:24 • F. M. Hidalgo-Sánchez et al. ACKNOWLEDGMENTS The authors would like to thank the Seville City Council’s Urban Planning Department, especially the Urban Conservation and Building Restoration Service, the Urban Planning and Development Service and the Seville Spatial Data Infrastructure (ide.SEVILLA). 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